FACTORS AFFECT THE APPLICATION OF DEEP-LEARNING CHATBOTS FOR ONLINE SHOPPING IN VIETNAM Các yếu tố tác động đến việc áp dụng deep-learning chatbot để mua sắm trực tuyến tại Việt Nam

Abstract

This research identifies, measures and highlights the importance of trust and attitude in influencing how people feel about and decide to use deep-learning chatbots to purchase online. Quantitative research methods are used to test models and study hypotheses. Data collected using Google Forms with 300 online retail customers in Vietnam were analyzed through structural equation modeling. The results suggest that perceived enjoyment and perceived social presence positively impact customers’ intention to use deep-learning chatbots both directly and indirectly through trust and attitude, except for perceived enjoyment’s non-effect on intention to use. This research offers a fresh perspective on deep-learning chatbot adoption, highlighting the crucial roles of trust, attitude and user perception in shaping decisions. By uncovering unexplored aspects of user interaction, it provides a unique lens for researchers to enhance the understanding and user experience with deep-learning chatbots in emerging technological landscapes. Managers are advised to prioritize strategies fostering transparency, reliability, enjoyable interactions, and recognize the potential of these chatbots in enhancing user experiences and driving successful purchasing, especially in an emerging market like Vietnam.